24/7 Apache Hudi Support
Eliminate Compaction Delays, Upsert Failures & Query Slowdowns
We are Open source Code Contributor
Zero-Day Vulnerability Fixes
Critical Vulnerability Assessment
Roadmap & Recommendations
SLA-Backed Technical Support
Zero-Day Vulnerability Fixes
Critical Vulnerability Assessment
Roadmap & Recommendations
SLA-Backed Technical Support
Apache Hudi Support That's Built to Meet the World's Strictest Data Lakehouse Standards.
En(AI)blingTM Success for Industry Leaders
Apache Hudi Support & Consulting Packages
Whether you run a single Hudi lakehouse or a large-scale multi-table environment across Spark and Flink, our plans are designed around your operational needs. As a leading Apache Hudi support company, we tailor every package to your infrastructure and SLA requirements.
Standard
Advanced
Platinum
Delivering Measurable Outcomes for Hudi-Driven Data Lakehouse Teams
Organizations across finance, e-commerce, media, and logistics trust Ksolves to optimize and support mission-critical Apache Hudi environments at scale.
99.99%
SLA Maintained
SLA Maintained
Ksolves holds 99.99% uptime across client environments through proactive monitoring, auto-healing pipelines, and zero-drama incident response.
40%
Lower TCO
Lower TCO
From licensing audits to compute consolidation, Ksolves cuts total cost of ownership by 40%, without cutting corners on performance or reliability.
98%
Contract Renewal Rate
Contract Renewal Rate
We take pride in saying 98% of clients come back. Not because of lock-in, but because the work speaks for itself. That’s Ksolves Promise - on time, on budget, and exactly what was promised.
30 Min
Turnaround Time
Turnaround Time
Ksolves responds and resolves in under 30 minutes, keeping production running and teams unblocked.
Apache Hudi Support Services to Keep Your Full Lakehouse Infrastructure Running
From COW table design and MOR compaction management to Apache Hudi 24×7 support and Hudi 1.x adoption, one team covers every layer of your lakehouse, so nothing falls between teams.
24×7 Table Operations, Fully Managed
Our certified engineers act as your dedicated Hudi operations team, managing COW and MOR table health, timeline integrity, and write configuration 24×7 so your data teams focus on analytics, not infrastructure failures.
- COW and MOR table design, provisioning, and lifecycle management
- Hudi timeline management: active, archived, and rollback operations
- Multi-writer conflict detection and resolution for concurrent upsert pipelines
- Partition management, key generation strategy, and record key design
- Automated backup and point-in-time restore using Hudi savepoints
- Table health reports: file size distribution, small file problem diagnosis
Early Detection for Compaction Bottlenecks
We build and operate the full Hudi compaction observability stack, detecting MOR log file bloat, clustering imbalance, and small file accumulation before they impact query performance or ingestion latency.
- Inline vs. async compaction strategy selection and configuration for MOR tables
- Clustering plan tuning: sort columns, partition-based clustering, and size targets
- Compaction lag monitoring with Prometheus, Grafana, and custom alerting
- Log file ratio and delta commit tracking with automated backpressure alerts
- File sizing optimization to eliminate small file problem at source.
- Compaction failure triage: rollback, repair, and re-trigger workflows
Compliance-Ready Security at Every Layer of Your Lakehouse
Ksolves applies defence-in-depth across access control, encryption, and audit logging for GDPR, HIPAA, PCI-DSS, and SOC 2 environments, ensuring your Hudi lakehouse meets enterprise data governance standards. Our enterprise support for Apache Hudi includes full compliance coverage from day one.
- Column-level and row-level access control via Apache Ranger integration
- Storage-layer encryption for S3, ADLS, and GCS-backed Hudi tables
- Audit trail configuration for all Hudi write, compaction, and clustering operations
- Data masking and tokenization for PII fields in Hudi tables
- GDPR right-to-erasure implementation using Hudi delete and upsert APIs
- Compliance reporting aligned with SOC 2, HIPAA, and GDPR requirements
Zero-Downtime Hudi Version Upgrades
Ksolves manages Hudi version upgrades and table format migrations with zero downtime, including Hudi 0.x to 1.x transitions, COW-to-MOR migrations, and cross-cloud lakehouse moves between S3, GCS, and ADLS.
- Pre-upgrade table compatibility audit and API deprecation assessment
- Hudi 0.x to 1.x migration: new timeline layout, metadata table changes
- COW-to-MOR table conversion for write-heavy workloads with zero data loss
- Cross-cloud Hudi table migration (S3 ↔ GCS ↔ ADLS) with partition validation
- Spark and Flink writer version alignment post-upgrade with regression testing
- Post-upgrade query performance benchmarking and sign-off documentation
Deep-Layer Hudi Performance Engineering
Ksolves debugs Apache Hudi performance issues at the table design, compaction, indexing, and Spark configuration layers — and fixes them at the root, not the symptom. We eliminate query slowdowns, upsert latency, and storage bloat measurably.
- Bloom filter and Simple index tuning for upsert lookup performance
- Hudi metadata table enablement to eliminate expensive file listing on S3/GCS
- Spark write config tuning: hoodie.upsert.shuffle.parallelism, bulk insert, and insert overwrite
- Partition pruning optimization for Hive Metastore and AWS Glue catalog
- Read-optimized vs. snapshot query selection guidance per use case
- MOR merge-on-read log block tuning to reduce read amplification
Schema Changes Without Disruption
Ksolves manages Hudi schema evolution operations and index strategy,, ensuring backward-compatible schema changes land cleanly, and that index configurations deliver measurable query speedups without write amplification.
- Schema evolution: adding, renaming, and nullable column changes without table rewrites
- Avro schema registry integration for schema versioning and compatibility enforcement
- BLOOM, SIMPLE, GLOBAL_BLOOM, and HBASE index type selection and configuration
- Hudi metadata table-based column stats index for file pruning acceleration
- Partition column strategy design: date-based, hash-based, and custom partitioning
- Incremental query design using beginInstantTime for CDC and audit pipelines
Incident Resolution and Root Cause Analysis
Production Hudi incidents are rarely simple. Ksolves traces every symptom writer conflicts, corrupt timelines, and compaction stalls to the actual root, closes it fast, and documents it so it never recurs.
- Emergency triage for corrupt Hudi timeline, failed compaction, and writer lock failures
- Multi-writer conflict investigation: optimistic concurrency control and lock provider diagnosis
- Rollback and restore operations for failed upsert batches and partial commits
- Incremental query failure diagnosis: missing commits, archived timeline gaps
- Spark OOM and shuffle failure analysis during large Hudi bulk insert operations
- Full written RCA for engineering review, compliance audit, and incident prevention
Through the Client's Lens
Why Ksolves is a Trusted Choice of Global Teams for Apache Hudi Support?
Ksolves combines deep Hudi expertise with SLA-backed support to deliver reliable, scalable, and production-ready lakehouse operations. As a dedicated Apache Hudi managed support provider, we're with your team around the clock, not just during incidents.
90%
Client Retention Rate
750+
Projects Successfully
Delivered
NSE & BSE
Publicly Listed
Company
600+
Workforce and still
growing
350+
Certifications
200+
Happy Clients
150K+
Support Hours
Completed
Industries We Help Scale with Apache Hudi
From real-time CDC pipelines to GDPR-compliant data lakes, Ksolves is a trusted Apache Hudi support services provider helping industries run lakehouses with maximum performance, reliability, and uptime.
Telecom
Ksolves manages real-time telecom data lakehouses, handling network telemetry upserts, CDR record deduplication, and Hudi table compaction across distributed infrastructure at carrier scale.
Healthcare
With deep experience in HIPAA-compliant Hudi environments, we manage patient record upsert pipelines, HL7 and FHIR data ingestion, and audit-ready incremental queries across clinical data lakes.
E-Commerce
Having worked across e-commerce data ecosystems, we keep order, inventory, and customer behaviour tables in real-time sync using Hudi CDC pipelines across every fulfilment channel.
Fintech
Understanding what fintech lakehouses demand, we manage Hudi environments built for transaction upserts, fraud signal ingestion, and regulatory reporting, where every record and every delete counts.
Entertainment
Working with entertainment platforms at scale, we support high-throughput Hudi tables for user engagement events, content metadata, and recommendation signal feeds that grow with audience demand.
Manufacturing
With hands-on manufacturing data experience, we connect shop floor sensor streams and MES systems into time-series Hudi tables with TTL-based data archival and efficient compaction.
Retail
Understanding retail data complexity, we manage Hudi environments connecting POS, loyalty, and customer data across physical and digital channels into consistent, query-ready lakehouse tables.
Banking & Financial
As a compliance-aware Hudi partner, we support banking institutions with GDPR-erasure-capable tables, encrypted lakehouses, and audit-ready pipelines for regulatory reporting across multiple jurisdictions.
Logistics & Supply Chain
With proven logistics data experience, we manage Hudi tables covering shipment state, warehouse telemetry, and carrier event streams — with incremental query support for real-time operational dashboards.
Technology & SaaS
Working alongside technology companies, we support Hudi tables that store multi-tenant event data, product analytics, and internal metrics across cloud-native S3 and GCS lakehouses without disruption.
Ksolves on Apache Hudi: Insights from Enterprise Experts
Explore the latest Apache Hudi trends, performance strategies, and expert insights for building scalable, reliable, and high-performing data lakehouse environments.
Success Stories from Global Enterprises
Discover real-world case studies showcasing measurable outcomes, faster performance, and successful digital transformation journeys.
Real-Time Fraud Detection for Telecom
Industry
Telecommunication
Technology
Apache Kafka · Apache Spark
3-5B
Daily marketing events processed in real time for a Telco operator, with burst fraud detected and suppressed within a 30-second window using Apache Kafka and Spark Structured Streaming.
Read More
Multi-Site CDR Pipeline for Telecom
Industry
Telecommunication
Technology
Apache NiFi · Apache Kafka · Apache Spark · Apache Druid
5 Sites
Unified under a single real-time CDR pipeline for a Middle East and Africa telecom operator, delivering sub-minute data availability, sub-second query response, and same-day billing anomaly detection.
Read More
NiFi 1.27 to 2.7 Kubernetes Migration
Industry
Financial Services
Technology
Apache NiFi 2.7 · Kubernetes · OneLogin SSO · Apache Airflow
6 Weeks
Full migration from Apache NiFi 1.27 to Kubernetes-native NiFi 2.7 completed for a financial services firm, with zero production downtime and every pipeline running cleanly on the new platform from day one.
Read More
Oil Well Master Data Deduplication
Industry
Energy, Oil & Gas
Technology
Azure Databricks · Apache Spark · Azure Data Factory · Azure Data Lake Gen2
900K
Duplicate oil well records eliminated from 6,200 Excel files for a US exploration and production company, delivering a single verified well master on Azure with a residual duplicate rate of just 1.4%.
Read More
MapR to ClickHouse CDR Migration
Industry
Telecommunication
Technology
Apache Spark · ClickHouse · Apache NiFi · Kubernetes
100%
Call records and compliance data migrated from a discontinued MapR platform to ClickHouse for a North African telecom operator, with zero data loss confirmed across every batch and compliance queries reduced from 6 hours to under 8 seconds.
Read More
Open Data Lakehouse on OpenShift
Industry
Retail
Technology
Apache NiFi · Apache Kafka · Apache Flink · Apache Iceberg · Trino · Red Hat OpenShift
16 TB
Daily real-time retail data processed with sub-second pricing and stock decisions for a major Middle East retailer, on existing Red Hat OpenShift infrastructure with zero new hardware and no Power BI report changes.
Read More
Real-Time Fraud Detection for Telecom
Industry
Telecommunication
Technology
Apache Kafka · Apache Spark
3-5B
Daily marketing events processed in real time for a Telco operator, with burst fraud detected and suppressed within a 30-second window using Apache Kafka and Spark Structured Streaming.
Read MoreMulti-Site CDR Pipeline for Telecom
Industry
Telecommunication
Technology
Apache NiFi · Apache Kafka · Apache Spark · Apache Druid
5 Sites
Unified under a single real-time CDR pipeline for a Middle East and Africa telecom operator, delivering sub-minute data availability, sub-second query response, and same-day billing anomaly detection.
Read MoreNiFi 1.27 to 2.7 Kubernetes Migration
Industry
Financial Services
Technology
Apache NiFi 2.7 · Kubernetes · OneLogin SSO · Apache Airflow
6 Weeks
Full migration from Apache NiFi 1.27 to Kubernetes-native NiFi 2.7 completed for a financial services firm, with zero production downtime and every pipeline running cleanly on the new platform from day one.
Read MoreOil Well Master Data Deduplication
Industry
Energy, Oil & Gas
Technology
Azure Databricks · Apache Spark · Azure Data Factory · Azure Data Lake Gen2
900K
Duplicate oil well records eliminated from 6,200 Excel files for a US exploration and production company, delivering a single verified well master on Azure with a residual duplicate rate of just 1.4%.
Read MoreMapR to ClickHouse CDR Migration
Industry
Telecommunication
Technology
Apache Spark · ClickHouse · Apache NiFi · Kubernetes
100%
Call records and compliance data migrated from a discontinued MapR platform to ClickHouse for a North African telecom operator, with zero data loss confirmed across every batch and compliance queries reduced from 6 hours to under 8 seconds.
Read MoreOpen Data Lakehouse on OpenShift
Industry
Retail
Technology
Apache NiFi · Apache Kafka · Apache Flink · Apache Iceberg · Trino · Red Hat OpenShift
16 TB
Daily real-time retail data processed with sub-second pricing and stock decisions for a major Middle East retailer, on existing Red Hat OpenShift infrastructure with zero new hardware and no Power BI report changes.
Read MoreFrequently Asked Questions
Quick answers to common questions about Hudi table management, performance, and ongoing support.
Comprehensive Apache Hudi support services cover the full operational lifecycle: table design (COW/MOR), compaction and clustering management, schema evolution, index tuning, version upgrades, GDPR erasure implementation, monitoring and alerting, and Apache Hudi 24×7 support for production lakehouse failures.
Copy-on-Write (COW) rewrites the entire Parquet file on every upsert, resulting in fast reads but slow writes. Merge-on-Read (MOR) appends delta logs alongside base files, enabling fast writes but requiring compaction to merge the logs for optimal read performance. Ksolves helps you choose the right table type based on your write frequency, query pattern, and latency requirements.
Compaction merges MOR delta log files into base Parquet files to keep read performance optimal. It fails most commonly due to Spark executor OOM from oversized compaction plans, lock provider timeouts from concurrent writers, corrupt log files from failed ingestion, or misconfigured async compaction schedules. Ksolves diagnoses and resolves all compaction failure modes as part of its managed support service.
Yes. Hudi supports soft deletes (null payload) and hard deletes via the delete API, allowing targeted removal of individual records by primary key across all partitions. Ksolves implements partition-aware erasure pipelines, audit logging, and compliance documentation to satisfy GDPR, CCPA, and similar right-to-erasure obligations at scale.
The small file problem occurs when high-frequency upserts create many tiny Parquet files per partition — degrading file listing, catalog scan, and query planning performance. It’s fixed by tuning hoodie.parquet.max.file.size, enabling auto-sizing, deploying clustering to consolidate files, and adjusting insert parallelism to match target file size targets. Ksolves resolves small file problems as part of its Hudi performance tuning service.
Apache Hudi tables are readable by Apache Spark (native), Apache Flink, Presto, Trino, Apache Hive, AWS Athena, Google BigQuery (via manifest), Impala, and Dremio. Ksolves supports integration and query optimization across all supported engines as part of its enterprise support for Apache Hudi.
Our SLAs guarantee critical issue acknowledgement within 30 minutes and resolution within 1–4 hours, depending on plan tier. Critical issues include compaction failures blocking ingestion, corrupt timelines, and writer lock failures, causing data loss risk. All SLAs are contractually backed and tracked in monthly compliance reports.
